This document discusses Bayes' theorem and its application. It begins with the formula P(H|E)= [P(E|H) P(H)]/P(E) and an example of using it to calculate the probability of a scientist given they are a farmer. It then explains the terms in Bayes' theorem - P(H) is the prior probability of a hypothesis, P(E|H) is the likelihood, P(E) is the marginal probability of evidence, and P(H|E) is the posterior probability. It ends with a quote about the importance of thinking like Bayesians and updating knowledge with new information.